Peyghami Saeed, Dragicevic Tomislav, Blaabjerg Frede
Department of Energy Technology, Aalborg University, 9220, Aalborg, Denmark.
Department of Electrical Engineering, Technical University of Denmark, 2800, Kgs. Lyngby, Denmark.
Sci Rep. 2021 Apr 6;11(1):7557. doi: 10.1038/s41598-021-87165-3.
This paper proposes a long-term performance indicator for power electronic converters based on their reliability. The converter reliability is represented by the proposed constant lifetime curves, which have been developed using Artificial Neural Network (ANN) under different operating conditions. Unlike the state-of-the-art theoretical reliability modeling approaches, which employ detailed electro-thermal characteristics and lifetime models of converter components, the proposed method provides a nonparametric surrogate model of the converter based on limited non-linear data from theoretical reliability analysis. The proposed approach can quickly predict the converter lifetime under given operating conditions without a further need for extended, time-consuming electro-thermal analysis. Moreover, the proposed lifetime curves can present the long-term performance of converters facilitating optimal system-level design for reliability, reliable operation and maintenance planning in power electronic systems. Numerical case studies evaluate the effectiveness of the proposed reliability modeling approach.
本文基于电力电子变换器的可靠性提出了一种长期性能指标。变换器的可靠性由所提出的恒定寿命曲线表示，这些曲线是在不同运行条件下使用人工神经网络（ANN）开发的。与采用变换器组件详细电热特性和寿命模型的最新理论可靠性建模方法不同，该方法基于理论可靠性分析的有限非线性数据提供了变换器的非参数替代模型。所提出的方法可以在给定运行条件下快速预测变换器寿命，而无需进一步进行耗时的扩展电热分析。此外，所提出的寿命曲线可以呈现变换器的长期性能，有助于电力电子系统中可靠性的优化系统级设计、可靠运行和维护规划。数值案例研究评估了所提出的可靠性建模方法的有效性。
